Named after IBM’s first CEO Thomas J. Watson, Watson is a supercomputer able to answer questions posed in natural language. It first became famous in early 2011 for beating a couple of the best players of Jeopardy in a 3 day streak game. He beat Ken Jennings and Brad Rutter, the first had 74 winnings in a row and the second had earned a total of $3.25 million. At the time Watson was about the size of a room. It was hot and very noisy because of the cooling systems. He was represented in the room by a simple avatar. Today, Watson has changed a lot. Now it is more business friendly and has lost a lot of weight. From a Jeopardy winning computer it has become a successful commercialized supercomputer. In the following chapters I will talk about its origins, its actual situation and a little bit about its future.
The Initial Idea
At IBM innovation is a very important thing. They are always looking for the next “Grand Challenge”. Generally this is done internally in the company. The projects aren’t created for the purpose of being commercialized. Their purpose is to put against each other humans and machines, and to inspire people to study, work and research in science.
A very famous example of such a project is the Deep Blue. Deep Blue was the machine who beat Garry Kasparov at chess. It is one of the cornerstones of the advances that have happened in the field of Artificial Intelligence.
These projects come to live in the Research division at IBM. In 2005 Paul Horn, director of the division wanted to try to create a machine able to pass the Turing Test. No machine had done it. But researchers didn’t believe that it would get the public’s attention in the way that Deep Blue had. Horn thought of another game where it would...
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...d Google are trying to do today with Siri and Google Voice. These services just look for keywords on the internet. Watson can do much more than that by giving relevant answers not just links to web-pages.
Conclusion
So Watson isn’t a big clunky supercomputer able to play a game anymore. It is much more than that. There are several versions of Watson at IBM that can be tailored to a specific purpose. They don’t take entire rooms anymore. Watson was optimized so much that it occupies just a small part of a server. So the uses of the supercomputer are infinite. Who knows what will be its future... maybe we should ask Watson itself.
Works Cited
http://money.cnn.com/2014/01/09/technology/enterprise/ibm-watson/
http://www.techrepublic.com/article/ibm-watson-the-inside-story-of-how-the-jeopardy-winning-supercomputer-was-born-and-what-it-wants-to-do-next/
Smarter than You Think starts out with a cautionary tale of how in 1997 world chess champion Garry Kasparov was beaten by Deep Blue, an I.B.M. supercomputer. This was a considered a milestone in artificial intelligence. If a computer could easily defeat a chess champion, what would happen to the game and its players? A year after Kasparov was defeated by the program he decided to see what would happen when a computer and person were paired up. He called this collaboration the centaur; A hybrid consisting of the algorithms and history logs of chess as well as the brain to “analyze their opponents’ strengths and weaknesses, as well as their moods.” ...
Turing starts his renowned paper “Computing Machinery and Intelligence” with a simple question: “I propose to consider the question, ‘Can machines think?’ ” He believed that in about fifty years (from his day), it will be possible to make computers play ‘the imitation game’ so well that an average interrogator will not have more than 70 percent chance of making the right identification after five minutes of questioning. He also predicted that the use of words and general educated opinion will have altered so much that one will be able to speak of machine thinking without expecting to be contradicted. However, modern computer technology regarding Artificial Intelligence hasn’t quite met the expectations Turing had made about 60 years ago. It is true that, and partly because, scientific advancements are slowing down as we get closer to science’s ‘limits’.
In this paper I will evaluate and present A.M. Turing’s test for machine intelligence and describe how the test works. I will explain how the Turing test is a good way to answer if machines can think. I will also discuss Objection (4) the argument from Consciousness and Objection (6) Lady Lovelace’s Objection and how Turing responded to both of the objections. And lastly, I will give my opinion on about the Turing test and if the test is a good way to answer if a machine can think.
The conditions of the present scenario are as follows: a machine, Siri*, capable of passing the Turing test, is being insulted by a 10 year old boy, whose mother is questioning the appropriateness of punishing him for his behavior. We cannot answer the mother's question without speculating as to what A.M. Turing and John Searle, two 20th century philosophers whose views on artificial intelligence are starkly contrasting, would say about this predicament. Furthermore, we must provide fair and balanced consideration for both theorists’ viewpoints because, ultimately, neither side can be “correct” in this scenario. But before we compare hypothetical opinions, we must establish operant definitions for all parties involved. The characters in this scenario are the mother, referred to as Amy; the 10 year old boy, referred to as the Son; Turing and Searle; and Siri*, a machine that will be referred to as an “it,” to avoid an unintentional bias in favor of or against personhood. Now, to formulate plausible opinions that could emerge from Turing and Searle, we simply need to remember what tenants found their respective schools of thought and apply them logically to the given conditions of this scenario.
Artificial Intelligence (AI) is one of the newest fields in Science and Engineering. Work started in earnest soon after World War II, and the name itself was coined in 1956 by John McCarthy. Artificial Intelligence is an art of creating machines that perform functions that require intelligence when performed by people [Kurzweil, 1990]. It encompasses a huge variety of subfields, ranging from general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on the crowded street, and diagnosing diseases. Artificial Intelligence is relevant to any intellectual task; it is truly a Universal field. In future, intelligent machines will replace or enhance human’s capabilities in
One of the hottest topics that modern science has been focusing on for a long time is the field of artificial intelligence, the study of intelligence in machines or, according to Minsky, “the science of making machines do things that would require intelligence if done by men”.(qtd in Copeland 1). Artificial Intelligence has a lot of applications and is used in many areas. “We often don’t notice it but AI is all around us. It is present in computer games, in the cruise control in our cars and the servers that route our email.” (BBC 1). Different goals have been set for the science of Artificial Intelligence, but according to Whitby the most mentioned idea about the goal of AI is provided by the Turing Test. This test is also called the imitation game, since it is basically a game in which a computer imitates a conversating human. In an analysis of the Turing Test I will focus on its features, its historical background and the evaluation of its validity and importance.
The official foundations for "artificial intelligence" were set forth by A. M. Turing, in his 1950 paper "Computing Machinery and Intelligence" wherein he also coined the term and made predictions about the field. He claimed that by 1960, a computer would be able to formulate and prove complex mathematical theorems, write music and poetry, become world chess champion, and pass his test of artificial intelligences. In his test, a computer is required to carry on a compelling conversation with humans, fooling them into believing they are speaking with another human. All of his predictions require a computer to think and reason in the same manner as a human. Despite 50 years of effort, only the chess championship has come true. By refocusing artificial intelligence research to a more humanlike, cognitive model, the field will create machines that are truly intelligent, capable of meet Turing's goals. Currently, the only "intelligent" programs and computers are not really intelligent at all, but rather they are clever applications of different algorithms lacking expandability and versatility. The human intellect has only been used in limited ways in the artificial intelligence field, however it is the ideal model upon which to base research. Concentrating research on a more cognitive model will allow the artificial intelligence (AI) field to create more intelligent entities and ultimately, once appropriate hardware exists, a true AI.
In a February two thousand and eleven game, Watson competed against some of Jeopardy’s brightest stars Brad Rutter and Ken Jennings. Both Mr. Rutter and Jennings lost miserably against the super computer. Watson’s performance was almost flawless although it did make a few un-slightly mistakes. Anyway, the performance was superb, and was greeted as a scientific breakthrough of artificial intelligence in computers and intellectual technologies. Many people, including Jennings and Rutter stated that they were one of the first “knowledge-industry workers put out of work by the new generation of thinking
Alan Mathison Turing was born in Paddington, London, on June 23, 1912. He was a precocious child and began his interests in science and mathematics at a young age, but was never concerned about other right-brain classes such as English. This continued until an important friend of his passed away and set Turing on a path to achieve what his friend could no longer accomplish. When his friend Christopher Morcom died, Turing was launched into thoughts in physics about the physical mind being embodied in matter and whether quantum-mechanical theory affects the traditional problem of mind and matter. Many say today that this was the beginnings of Turing’s Turning Machine and the test still used today for artificial intelligence, the Turing Test.
This means that IBM has to be very careful with their strategy on protecting these patents. Thus, IBM has licenced their patents to create a revenue through the licencing fees. According to IP Magazine, 2012 IBM earned over $1 billion in licensing fees from its patents. This strategy has created a large amount of extra revenue, which has enabled IBM to invest more money in to areas such as research and development. Moreover, Watson innovation, protected by patents is driving new product value, new market, and new choices for the public, and new jobs, which all contributes to IBM’s product, service and IP licensing returns. (Intellectual Property IBM, 2014). These strategies that IBM use to protect its innovations are very effective and can be sure to protect their inventions in the future.
As my first point I would like to comment on the use of Watson as a
There are expert systems that can solve complex problems that humans train their whole lives for. In 1997, IBM's Deep Blue defeated the world champion in a game of chess (Karlgaard, p43). Expert systems design buildings, configure airplanes, and diagnose breathing problems. NASA's Deep Space One probe left with software that lets the probe diagnose problems and fix itself (Lyons).
Upbin, Bruce. "IBM's Watson Gets Its First Piece Of Business In Healthcare." Forbes. Forbes Magazine, 08 Feb. 2013. Web. 17 Mar. 2014.
...on, adaptation, and planning for the future. The computer is unable to win because it cannot think like a human, and that is why we humans are smarter than computers to this day (The Daily Galaxy 1-3).
Through a robot body, one can utilize AI algorithms to portray individual thinking. The first general purpose robot is called Shakey. Developed at the Stanford Research Institute from 1966 to 1972, Shakey was the first robot to think in advance. For example, Shakey was able to understand a command such as turn off a light switch in a particular room. The robot would go through a corridor, find the room and then locate and turn off a light switch. Shakey could complete an action without the need of step-by-step instructions. The LISP software was used to program Shakey. The development of Shakey advanced AI concepts from the invention of the A search algorithm to the understanding of the full capabilities of robots. Shakey raised the public’s awareness of computer science and artificial intelligence in the 1970s. Shakey moved public thoughts to questioning what machines could and will do in the future. (Artificial Intelligence and Robotics , 2015) To further the public’s thoughts about machine intelligence is IBM’s Deep Blue Computer. Deep Blue won a chess competition against famous chess champion Garry Kasparov. Deep Blue’s win was one of the first real instances of the competition of humans versus